Receivers' responses are integrated into costly third-party punishment in a way that interacts with the unfairness of allocations.

Costly third-party punishment (TPP) is an effective way to enforce fairness norms and promote cooperation. Recent studies have shown that the third party considers not only the proposer's suggested allocation but also the receiver's response to the allocation, which was typically ignored in traditional TPP studies when making punishment decisions. However, it remains unclear whether and how the varying unfair allocations and receivers' responses are integrated into third-party punishment. The current study addressed these issues at behavioral and electrophysiological levels by employing a modified third-party punishment task involving proposers' highly or moderately unfair allocations and the receivers' acceptance or rejection responses. At the behavioral level, participants punished proposers more often when receivers rejected relative to accepted unfair allocations. This effect was further modulated by the unfairness degree of allocations, indicated by a more pronounced rejection-sensitive effect when participants observed the moderately unfair offers. Electrophysiologically, when the receiver rejected the moderately unfair allocations, a stronger late-stage component P300/LPP, which was considered to be involved in allocations of attention resources, was found. Meanwhile, separated from the P300/LPP, the P200 associated with early attention capture demonstrated a rejection-sensitive effect that was independent of the unfairness degree of allocations. Together, in the costly TPP studies, the receiver is typically designated as passive and silent, and her/his responses to unfairness are conventionally ignored. However, our results indicate that except for the proposer's distribution behavior, the receiver's response does have an impact on third-party punishment in a way that interacts with the unfairness of allocations.

Single-cell transcriptomics reveals writers of RNA modification-mediated immune microenvironment and cardiac resident Macro-MYL2 macrophages in heart failure.

BACKGROUND: Heart failure (HF), which is caused by cardiac overload and injury, is linked to significant mortality. Writers of RNA modification (WRMs) play a crucial role in the regulation of epigenetic processes involved in immune response and cardiovascular disease. However, the potential roles of these writers in the immunological milieu of HF remain unknown. METHODS: We comprehensively characterized the expressions of 28 WRMs using datasets GSE145154 and GSE141910 to map the cardiac immunological microenvironment in HF patients. Based on the expression of WRMs, the immunological cells in the datasets were scored. RESULTS: Single-cell transcriptomics analysis (GSE145154) revealed immunological dysregulation in HF as well as differential expression of WRMs in immunological cells from HF and non-HF (NHF) samples. WRM-scored immunological cells were positively correlated with the immunological response, and the high WRM score group exhibited elevated immunological cell infiltration. WRMs are involved in the differentiation of T cells and myeloid cells. WRM scores of T cell and myeloid cell subtypes were significantly reduced in the HF group compared to the NHF group. We identified a myogenesis-related resident macrophage population in the heart, Macro-MYL2, that was characterized by an increased expression of cardiomyocyte structural genes (MYL2, TNNI3, TNNC1, TCAP, and TNNT2) and was regulated by TRMT10C. Based on the WRM expression pattern, the transcriptomics data (GSE141910) identified two distinct clusters of HF samples, each with distinct functional enrichments and immunological characteristics. CONCLUSION: Our study demonstrated a significant relationship between the WRMs and immunological microenvironment in HF, as well as a novel resident macrophage population, Macro-MYL2, characterized by myogenesis. These results provide a novel perspective on the underlying mechanisms and therapeutic targets for HF. Further experiments are required to validate the regulation of WRMs and Macro-MYL2 macrophage subtype in the cardiac immunological milieu.

The causal relationship between diet habits and cholelithiasis: a comprehensive Mendelian randomization (MR) study.

Background: Epidemiological studies show dietary habits can have an impact on the risk of cholelithiasis, but the relationship is still unclear. We used a comprehensive Mendelian randomization (MR) study to explore the relationship between dietary habits and cholelithiasis. Methods: The 18 dietary habits were divided into six categories: meat foods, cereals, vegetables, fruits, dairy products, beverages, and condiments. Cholelithiasis data came from a GWAS meta-analysis and the FinnGen consortium. The inverse variance weighted (IVW), the weighted median (WM), and MR-Egger approaches were used as the main MR analysis methods. In addition, multiple sensitivity analysis and meta-analysis were performed to verify the robustness of the results. Results: Dried fruit intake [odds ratio (OR) = 0.568; 95% confidence interval (CI), 0.405-0.797; p = 0.001] was discovered to reduce the risk of cholelithiasis. The sensitivity analysis and meta-analysis showed reliable results for the relationship between dried fruit intake and cholelithiasis. Conclusion: Our study found that dried fruit intake is a protective factor in the development of cholelithiasis. However, the mechanisms of action need to be further explored.

Characterization of ovarian progenitor cells for their potential to generate steroidogenic theca cells in vitro.

In brief: Progenitor cells with ovulation-related tissue repair activity were identified with defined markers (LGR5, EPCR, LY6A, and PDGFRA), but their potentials to form steroidogenic cells were not known. This study shows that the cells can generate progenies with different steroidogenic activities. Abstract: Adult mammalian ovaries contain stem/progenitor cells necessary for folliculogenesis and ovulation-related tissue rupture repair. Theca cells are recruited and developed from progenitors during the folliculogenesis. Theca cell progenitors were not well defined. The aim of current study is to compare the potentials of four ovarian progenitors with defined markers (LY6A, EPCR, LGR5, and PDGFRA) to form steroidogenic theca cells in vitro. The location of the progenitors with defined makers was determined by immunohistochemistry and immunofluorescence staining of ovarian sections of adult mice. Different progenitor populations were purified by magnetic-activated cell sorting (MACS) and/or fluorescence-activated cell sorting (FACS) techniques from ovarian cell preparation and were tested for their abilities to generate steroidogenic theca cells in vitro. The cells were differentiated with a medium containing LH, ITS, and DHH agonist for 12 days. The results showed that EPCR+ and LGR5+ cells primarily distributed along the ovarian surface epithelium (OSE), while LY6A+ cells distributed in both the OSE and parenchyma. However, PDGFRA+ cells were exclusively located in interstitial compartment. When the progenitors were purified by these markers and differentiated in vitro, LY6A+ and PDGFRA+ cells formed steroidogenic cells expressing both CYP11A1 and CYP17A1 and primarily producing androgens, showing characteristics of theca-like cells, while LGR5+ cells generated steroidogenic cells devoid of CYP17A1 expression and androgen production, showing a characteristic of progesterone-producing cells (granulosa- or lutea-like cells). In conclusion, progenitors from both OSE and parenchyma of adult mice are capable of generating steroidogenic cells with different steroidogenic capacities, showing a possible lineage preference.

PhbZIP2 regulates photosynthesis-related genes in an intertidal macroalgae, Pyropia haitanensis, under stress.

Intertidal macroalgae are important research subjects in stress biology. Basic region-leucine zipper transcription factors (bZIPs) play an important regulatory role in the expression of target genes under abiotic stress. We herein identified a bZIP2 gene PhbZIP2 to regulate abiotic stress tolerance in Pyropia haitanensis, a representative intertidal macroalgal species. Cloning and sequencing of the cDNA characterized a BRLZ structure and an α coiled-coil structure between amino acids and Expression of PhbZIP2 was detected to upregulate under both high temperature and salt stresses. A DAP-seq analysis revealed the PhbZIP2-binding motifs of (T/C)TCCA(C/G) and A (A/G)AAA (G/A), which differed from the conserved motifs in plants. Overexpression of PhbZIP2 was indicative of a high temperature and salt stress tolerances in transgenic Chlamydomonas reinhardtii. It was suggested that PhbZIP2 was probably involved in regulating expression of the photosynthetic-related genes and the response to the abiotic stresses in P. haitanensis, which provide new insights for elucidating efficient adaptation strategies of intertidal macroalgae.

Chrysin Inhibits TAMs-Mediated Autophagy Activation via CDK1/ULK1 Pathway and Reverses TAMs-Mediated Growth-Promoting Effects in Non-Small Cell Lung Cancer.

The natural flavonoid compound chrysin has promising anti-tumor effects. In this study, we aimed to investigate the mechanism by which chrysin inhibits the growth of non-small cell lung cancer (NSCLC). Through in vitro cell culture and animal models, we explored the impact of chrysin on the growth of NSCLC cells and the pro-cancer effects of tumor-associated macrophages (TAMs) and their mechanisms. We observed that M2-TAMs significantly promoted the growth and migration of NSCLC cells, while also markedly activating the autophagy level of these cells. Chrysin displayed a significant inhibitory effect on the growth of NSCLC cells, and it could also suppress the pro-cancer effects of M2-TAMs and inhibit their mediated autophagy. Furthermore, combining network pharmacology, we found that chrysin inhibited TAMs-mediated autophagy activation in NSCLC cells through the regulation of the CDK1/ULK1 signaling pathway, rather than the classical mTOR/ULK1 signaling pathway. Our study reveals a novel mechanism by which chrysin inhibits TAMs-mediated autophagy activation in NSCLC cells through the regulation of the CDK1/ULK1 pathway, thereby suppressing NSCLC growth. This discovery not only provides new therapeutic strategies for NSCLC but also opens up new avenues for further research on chrysin.

Transcriptomic characterization of interactions between sodium selenite and coenzyme Q10 on preventing cadmium-induced testicular defects.

The effect of heavy metal cadmium (Cd) on testicular function is recognized. However, the mechanism involved is not well-established. In the present study, we analyzed the testicular transcriptomic changes induced by acute Cd exposure of adult rats with and without supplementation of antioxidants selenium (Se) and/or coenzyme Q10 (CoQ). Cd significantly decreased serum testosterone and two steroidogenic proteins SCARB1 and STAR. RNA-Seq analyses of testicular RNAs revealed specific activation of oxidative stress-, inflammation-, MAPK- and NF-κB-related signaling molecules. In addition, Cd treatment down-regulated gene for I, III and IV complexes of mitochondrial electron transport chain and up-regulated genes for NADPH-oxidase, major cascade in ROS production. The decrease in steroidogenesis and increase in inflammation may result from oxidative stress since supplementation of Se and CoQ, but not with either alone, almost completely prevented these changes, including overall alterations in transcriptome. Cd exposure induced total of 1192 differentially expressed genes (DEGs), which was reduced to 29 without considering confounding factors associated with Se/CoQ, a 97.6% protection rate. In conclusion, Cd exposure inhibited Leydig cell steroidogenesis by down-regulating SCARB1 and STAR through increasing oxidative stress and inflammation, but Se plus CoQ synergistically prevented all the changes induced by the Cd exposure.

Risk factors and drug discovery for cognitive impairment in type 2 diabetes mellitus using artificial intelligence interpretation and graph neural networks.

Background: Among the 382 million diabetic patients worldwide, approximately 30% experience neuropathy, and one-fifth of these patients eventually develop diabetes cognitive impairment (CI). However, the mechanism underlying diabetes CI remains unknown, and early diagnostic methods or effective treatments are currently not available. Objective: This study aimed to explore the risk factors for CI in patients with type 2 diabetes mellitus (T2DM), screen potential therapeutic drugs for T2DM-CI, and provide evidence for preventing and treating T2DM-CI. Methods: This study focused on the T2DM population admitted to the First Affiliated Hospital of Hunan College of Traditional Chinese Medicine and the First Affiliated Hospital of Hunan University of Chinese Medicine. Sociodemographic data and clinical objective indicators of T2DM patients admitted from January 2018 to December 2022 were collected. Based on the Montreal Cognitive Assessment (MoCA) Scale scores, 719 patients were categorized into two groups, the T2DM-CI group with CI and the T2DM-N group with normal cognition. The survey content included demographic characteristics, laboratory serological indicators, complications, and medication information. Six machine learning algorithms were used to analyze the risk factors of T2DM-CI, and the Shapley method was used to enhance model interpretability. Furthermore, we developed a graph neural network (GNN) model to identify potential drugs associated with T2DM-CI. Results: Our results showed that the T2DM-CI risk prediction model based on Catboost exhibited superior performance with an area under the receiver operating characteristic curve (AUC) of 0.95 (specificity of 93.17% and sensitivity of 78.58%). Diabetes duration, age, education level, aspartate aminotransferase (AST), drinking, and intestinal flora were identified as risk factors for T2DM-CI. The top 10 potential drugs related to T2DM-CI, including Metformin, Liraglutide, and Lixisenatide, were selected by the GNN model. Some herbs, such as licorice and cuscutae semen, were also included. Finally, we discovered the mechanism of herbal medicine interventions in gut microbiota. Conclusion: The method based on Interpreting AI and GNN can identify the risk factors and potential drugs associated with T2DM-CI.

Learning from in-group and out-group models induces separative effects on human mate copying.

Mate copying is a social learning process in which individuals gather public information about potential mates by observing models' choices. Previous studies have reported that individual attributes of female models affect mate copying, yet little is known about whether and how the group attributes of models influence mate copying. In the current behavioral and functional magnetic resonance imaging studies, female participants were asked to rate their willingness to choose the depicted males as potential romantic partners before and after observing in-group or out-group female models accepting, rejecting or being undecided (baseline) about the males. Results showed that participants changed their ratings to align with the models' acceptance or rejection choices. Compared to rejection copying, the effect of acceptance copying was stronger and regulated by in- and out-group models, manifesting a discounting copying effect when learning from out-group models. At the neural level, for acceptance copying, stronger temporoparietal junction (TPJ) activity and connectivity between TPJ and anterior medial prefrontal cortex (amPFC) were observed when female models belonged to out-group members; meanwhile, the functional connection of TPJ and amPFC positively predicted the rating changes when learning from out-group models. The results indicated that participants might need more resources to infer out-group members' intentions to overcome the in-group bias during acceptance copying.

Are the original SARS-CoV-2 novel mutants from in vitro culture able to escape the immune response?

Monitoring variations in the virus genome to understand the SARS-CoV-2 evolution and spread of the virus is extremely important. Seven early SARS-CoV-2 isolates in China were cultured in vitro and were analyzed for their viral infectivity through viral growth assay, tissue culture infectious dose (TCID50 ) assay, spike protein quantification, and next generation sequencing analysis, and the resultant mutations in spike protein were used to generate the corresponding pseudoviruses for analysis of immune escape from vaccination and postinfection immunity. The results revealed that in vitro cultured SARS-CoV-2 virus had much higher mutation frequency (up to ~20 times) than that in infected patients, suggesting that SARS-CoV-2 diversify under favorable conditions. Monitoring viral mutations is not only helpful for better understanding of virus evolution and virulence change, but also the key to prevent virus transmission and disease progression. Compared with the D614G reference strain, a pseudovirus strain of SARS-CoV-2 was constructed with a high mutation rate site on the spike protein. We found some novel spike mutations during in vitro culture, such as E868Q, conferred further immune escape ability.

Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses.

Infectious diseases, like COVID-19, pose serious challenges to university campuses, which typically adopt closure as a non-pharmaceutical intervention to control spread and ensure a gradual return to normalcy. Intervention policies, such as remote instruction (RI) where large classes are offered online, reduce potential contact but also have broad side-effects on campus by hampering the local economy, students' learning outcomes, and community wellbeing. In this paper, we demonstrate that university policymakers can mitigate these tradeoffs by leveraging anonymized data from their WiFi infrastructure to learn community mobility-a methodology we refer to as WiFi mobility models (WiMob). This approach enables policymakers to explore more granular policies like localized closures (LC). WiMob can construct contact networks that capture behavior in various spaces, highlighting new potential transmission pathways and temporal variation in contact behavior. Additionally, WiMob enables us to design LC policies that close super-spreader locations on campus. By simulating disease spread with contact networks from WiMob, we find that LC maintains the same reduction in cumulative infections as RI while showing greater reduction in peak infections and internal transmission. Moreover, LC reduces campus burden by closing fewer locations, forcing fewer students into completely online schedules, and requiring no additional isolation. WiMob can empower universities to conceive and assess a variety of closure policies to prevent future outbreaks.

Effects of aging and macrophages on mice stem Leydig cell proliferation and differentiation in vitro.

Background: Testosterone plays a critical role in maintaining reproductive functions and well-beings of the males. Adult testicular Leydig cells (LCs) produce testosterone and are generated from stem Leydig cells (SLCs) during puberty through adulthood. In addition, macrophages are critical in the SLC regulatory niche for normal testicular function. Age-related reduction in serum testosterone contributes to a number of metabolic and quality-of-life changes in males, as well as age-related changes in immunological functions. How aging and testicular macrophages may affect SLC function is still unclear. Methods: SLCs and macrophages were purified from adult and aged mice via FACS using CD51 as a marker protein. The sorted cells were first characterized and then co-cultured in vitro to examine how aging and macrophages may affect SLC proliferation and differentiation. To elucidate specific aging effects on both cell types, co-culture of sorted SLCs and macrophages were also carried out across two ages. Results: CD51+ (weakly positive) and CD51++ (strongly positive) cells expressed typical SLC and macrophage markers, respectively. However, with aging, both cell types increased expression of multiple cytokine genes, such as IL-1b, IL-6 and IL-8. Moreover, old CD51+ SLCs reduced their proliferation and differentiation, with a more significant reduction in differentiation (2X) than proliferation (30%). Age matched CD51++ macrophages inhibited CD51+ SLC development, with a more significant reduction in old cells (60%) than young (40%). Crossed-age co-culture experiments indicated that the age of CD51+ SLCs plays a more significant role in determining age-related inhibitory effects. In LC lineage formation, CD51+ SLC had both reduced LC lineage markers and increased myoid cell lineage markers, suggesting an age-related lineage shift for SLCs. Conclusion: The results suggest that aging affected both SLC function and their regulatory niche cell, macrophages.

Rapid Determination of Polysaccharides in Cistanche Tubulosa Using Near-Infrared Spectroscopy Combined with Machine Learning.

BACKGROUND: Cistanche tubulosa, as a homology of medicine and food, not only has a unique medicinal value but also is widely used in healthcare products. Polysaccharide is one of its important quality indicators. OBJECTIVE: In this study, an analytical model based on near-infrared (NIR) spectroscopy combined with machine learning was established to predict the polysaccharide content of C. tubulosa. METHODS: The polysaccharide content in the samples determined by the phenol-sulfuric acid method was used as a reference value, and machine learning was applied to relate the spectral information to the reference value. Dividing the samples into a calibration set and a prediction set using the Kennard-Stone algorithm. The model was optimized by various preprocessing methods, including Savitzky-Golay (SG), standard normal variate (SNV), multiple scattering correction (MSC), first-order derivative (FD), second-order derivative (SD), and combinations of them. Variable selection was performed through the successive projections algorithm (SPA) and stability competitive adaptive reweighted sampling (sCARS). Four machine learning models were used to build quantitative models, including the random forest (RF), partial least-squares (PLS), principal component regression (PCR), and support vector machine (SVM). The evaluation indexes of the model were the coefficient of determination (R2), root-mean-square error (RMSE), and residual prediction deviation (RPD). RESULTS: RF performs best among the four machine learning models. R2c （calibration set coefficient of determination） and RMSEC （root mean square error of the calibration set）, %, were 0.9763. and 0.3527 for calibration, respectively. R2p （prediction set coefficient of determination）, RMSEP （root mean square error of the prediction set）, %, and RPD were 0.9230, 0.5130, and 3.33 for prediction, respectively. CONCLUSION: The results indicate that NIR combined with the RF is an effective method applied to the quality evaluation of the polysaccharides of C. tubulosa. HIGHLIGHTS: Four quantitative models were developed to predict the polysaccharide content in C. tubulosa, and good results were obtained. The characteristic variables were basically determined by the sCARS algorithm, and the corresponding characteristic groups were analyzed.

Evaluation of humoral immune responses induced by different SARS-CoV-2 spike trimers from wild-type and emerging variants with individual, sequential, and combinational delivered strategies.

The spike trimer of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an effective target for inducing neutralizing antibodies by coronavirus disease 2019 (COVID-19) vaccines. However, the diversity of spike protein from emerging SASR-CoV-2 variants has become the major challenge for development of a universal vaccine. To investigate the immunogenicity of spike proteins from various circulating strains including wild type, Delta, and Omicron variants, we produced various natural spike trimers and designed three vaccination strategies, that is, individual, sequential, and bivalent regimens to assess autologous and heterogenous antibody responses in a mouse model. The results indicated that monovalent vaccine strategy with individual spike trimer could only induce binding and neutralizing antibodies against homologous viruses. However, sequential and bivalent immunization with Delta and Omicron spike trimers could induce significantly broader neutralizing antibody responses against heterogenous SARS-CoV-2. Interestingly, the spike trimer from Omicron variant showed superior immunogenicity in inducing antibody response against recently emerging XE variant. Taken together, our data supported the development of novel vaccination strategies or multivalent vaccine against emerging variants.

Isolation of Leydig cells from adult rat testes by magnetic-activated cell sorting protocol based on prolactin receptor expression.

BACKGROUND: The primary function of testicular Leydig cells (LCs) is to produce testosterone (T). In vitro culture of the cells represents a very important approach to study androgen production and its regulations. Various methods have been developed for the enrichment of the cells from the testes. However, getting cells in large numbers with high purity and viability is still challenging. Here, we describe a new way to isolate LCs from rat testes in large quantity with high purity and viability. METHODS: Enzymatic digested testicular cells from adult rats were labelled with prolactin receptor (PRLR) antibody. The positive cells were isolated by magnetic-activated cell sorting (MACS) protocol. Purified LCs were tested in vitro for their steroidogenic (T production) and non-steroidogenic (25-OH-vitamin D production and Insl3 and Cyp2r1expressions) functions in the presence of Luteinizing Hormone (LH) for up to 24 h. RESULTS: Reanalysis of scRNA-seq data indicates that Prlr expression is highly specific in LCs of adult rat testis. MACS procedure based on PRLR expression was able to isolate LCs with very high yield (about 106 cells/testis), high purity (about 95%) and viability (> 93%). Purified LCs retained high steroidogenic and non-steroidogenic functions in responding to maximal LH stimulations, with more than 10-fold increases in T production in 3 h and 42% and 103% increases in Insl3 and Cyp2r1 expressions in 24 h. DISCUSSION AND CONCLUSION: We have established an excellent way to purify high quality LCs from adult rat testis that can serve as a useful tool to study the physiology, pharmacology and toxicology of the cells in vitro.

Single-cell RNA sequencing of adult rat testes after Leydig cell elimination and restoration.

Spermatogenesis is an efficient, complex, and highly organized proliferation and differentiation process that relies on multiple factors including testosterone produced by the Leydig cells. Although the critical role played by testosterone in spermatogenesis is well recognized, the mechanism by which it works is still not completely understood, partially due to the inability to specifically and precisely monitor testosterone-dependent changes within developing germ cells. Here we present single-cell RNA sequencing data from10,983 adult rat testicular cells after the rats were treated with ethanedimethanesulfonate, which temporarily eliminates Leydig cells. The elimination and recovery of Leydig cells represented a complete testosterone depletion and restoration cycle. The dataset, which includes all developing germ cells from spermatogonia to spermatozoa, should prove useful for characterizing developing germ cells, their regulatory networks, and novel cell-specific markers. The dataset should be particularly useful for exploring the effects of the androgen environment on the regulation of spermatogenesis. As this is the first single-cell RNA-Seq dataset for rat testes, it can also serve as a reference for future studies.

Identification of Rat Testicular Leydig Precursor Cells by Single-Cell-RNA-Sequence Analysis.

Stem Leydig cells (SLCs) play a critical role in the development and maintenance of the adult Leydig cell (ALC) population. SLCs also are present in the adult testis. Their identification, characteristics, and regulation in the adult testis remain uncertain. Using single-cell RNA-seq, we found that the mesenchymal stromal population may be involved in ALC regeneration. Upon ALC elimination, a fraction of stromal cells begins to proliferate while a different fraction begins to differentiate to ALCs. Transcriptomic analysis identified five stromal clusters that can be classified into two major groups representing proliferation and differentiation populations. The proliferating group represents stem cells expressing high levels of CD90, Nes, Lum, Fn and Gap43. The differentiating group represents a progenitor stage that is ready to form ALCs, and specifically expresses Vtn, Rasl11a, Id1 and Egr2. The observation that the actively dividing cells after ALC loss were not those that formed ALCs suggests that stem cell proliferation and differentiation are regulated separately, and that the maintenance of the stromal stem cell pool occurs at the population level. The study also identified specific markers for the major interstitial cell groups and potential paracrine factors involved in the regulation of SLCs. Our data suggest a new theory about SLC identity, proliferation, differentiation, and regulation.

Circulating long non-coding RNA TTTY15 and HULC serve as potential novel biomarkers for predicting acute myocardial infarction.

INTRODUCTION: Acute myocardial infarction (AMI) is a ubiquitous cardiovascular disease ensuing adverse prognosis caused by myocardial necrosis. Effective and rapid diagnosis of AMI is essential to following treatment in clinical practice while the existed biomarkers have inherent limitations. Consequently, exploration of novel biomarkers is needed. Long noncoding RNA (lncRNA) emerges as the upcoming biomarkers adopted in clinical use, and we aim at investigating the diagnostic power of lncRNA TTTY15 and HULC in AMI patients. METHOD: We measured lncRNA level in 80 AMI patients and 36 healthy volunteers in discovering cohort and 50 AMI patients and 20 healthy volunteers in verification cohort with quantitative RT-PCR method. Receiver operating characteristic (ROC) analysis was administered to detect the diagnostic power of selected lncRNAs. Regression and correlation analyses were performed to explore the related factors. RESULTS: ROC analysis reveals the superiority of TTTY15 and HULC as biomarkers against conventional AMI biomarkers CKMB (AUC of TTTY15: 0.915 versus CKMB: 0.768 versus TnT: 0.869); AUC of HULC: 0.905 versus CKMB: 0.768 versus TnT: 0.869). Regression and correlation analysis indicates that TTTY15 and HULC may be one of the contributing factors to AMI and related to accepted risk factors. CONCLUSION: Our results revealed the diagnostic potency of lncRNA TTTY15 and HULC, and they could also be treated as novel therapeutic targets in AMI therapy, hinting inspiration to the cardiologist in clinical practice.